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Can AI learn to grade endoscopy quality from video?

NCT ID NCT06822816

Knowledge-focused Sponsor: Centre hospitalier de l'Université de Montréal (CHUM) Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now This study
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Aug 11, 2026 · Last updated Aug 12, 2026 · Updated 1 time

Summary

This study aims to create a large library of recorded endoscopy procedures from adults undergoing upper or lower gastrointestinal exams. The goal is to use these videos to develop and validate artificial intelligence tools that can automatically detect and report quality metrics, such as how thoroughly the procedure was performed. The library may also help create educational modules to train future endoscopists. By collecting diverse procedure data, researchers hope to build AI systems that provide real-time feedback and improve overall endoscopy quality.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
Artificial intelligence-empowered endoscopy quality reporting and educational modules
What this could lead to
If successful, this could lead to AI tools that automatically assess endoscopy quality, improve training for doctors, and potentially enhance detection of polyps and other abnormalities.
What could go wrong
This is an observational study, so it does not test a treatment. The AI models may not perform as expected in real-world settings, and the library's diversity may be limited.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 10,000 people

The number the study aims to enrol. It can still change while the study runs.

Started

Jun 2022

Expected to finish

Dec 2028

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

All eligible patients presenting at the CHUM for an upper or lower endoscopy will be approached for this study.

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * ≥ 18 y.o. * indication of undergoing a screening, surveillance, diagnostic, or therapeutic upper (EGD) or lower (colonoscopy) endoscopy Exclusion Criteria: * Coagulopathy defined as an elevated INR ≥ 2.5 * Platelet count ≤ 50,000/mm3 * Emergency endoscopy * Poor general health defined as the American Society of Anesthesiologists physical status class \>3

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Conditions

The condition(s) this trial relates to.

inflammatory bowel disease polyp of colon rectal cancer

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Artificial intelligence (AI) Polyp of colon

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    1 site. The list below names each one and where it is.

  2. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  3. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

Contacts and locations

Locations

  • Centre Hospitalier de l'Université de Montréal

    RECRUITING

    Montreal, Quebec, Canada

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